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Record W2007977984 · doi:10.5539/cis.v2n3p161

Study on the Multiple-Key-Pair Generation Scheme Based on Grey Half-generation

2009· article· en· W2007977984 on OpenAlex
Peng Li, Yulian Shang, Jifeng Wang, Yufei Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComputer and Information Science · 2009
Typearticle
Languageen
FieldComputer Science
TopicChaos-based Image/Signal Encryption
Canadian institutionsnot available
Fundersnot available
KeywordsKey generationComputer scienceKey (lock)EncryptionScheme (mathematics)Key spaceSet (abstract data type)Key encapsulationKey managementAlgorithmsortTheoretical computer sciencePublic-key cryptographyKey distributionComputer networkComputer securityMathematicsInformation retrieval

Abstract

fetched live from OpenAlex

The generation of the multi-key-pair in the RSA iterative encryption system was studied, and from the generation algorithm of key, a sort of multi-key-pair generation scheme was proposed in the article. In the scheme, the encryption key set and the decryption key set used in the encryption system were managed by the improved half-generation algorithm, and the management scheme that one secrete key was used to generate multiple key pairs could solve the difficult management problem for multiple key sets. Finally, the key generation algorithm was simulated by VB6.0 in the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.008
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.264
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it